Hy Memory

Hy Memory is a memory engine and Python SDK (hy-memory) from Tencent Hunyuan for self-evolving LLM agents. It provides separate memory pipelines for chat, productivity work, and software engineering. The repository also includes MemHub, a local-first desktop and CLI product built on top of it.

What It Is

Hy Memory is a library that agents call to write and search long-term memory. It needs only an LLM endpoint and an embedding endpoint, and any OpenAI-compatible service works. Users call add() with plain text or OpenAI-format messages and search() to retrieve memories, with CRUD operations and an evolve() call also available.

Three Memory Scenes

The chat scene organizes personal memory into a hierarchy from raw conversation through atomic facts, session summaries, schemas, and prospective intentions. The working scene records a session's facts plus reusable experiences, based on a tool-call trace. The coding scene uses the same two layers and adds a version-evolution chain that stores the real diff of each code revision, sourced from local Git diffs or replace actions in the tool trace. When scene is omitted, automatic routing classifies writes that include tool calls.

Modes and Storage

The lite mode does raw embedding writes and searches with no LLM calls. The pro mode adds LLM extraction and reconciliation. The ultra mode adds System 2 schema induction and a cross-domain sweeper triggered by evolve(). Vector stores include ChromaDB, Qdrant, and FAISS, and graph stores include Kuzu and Neo4j. Working and coding metadata live in local SQLite.

MemHub and Integrations

MemHub unifies conversation history and coding traces from user-authorized AI applications such as Claude Code, Cursor, Codex, OpenCode, and Qwen Code into one local data directory for governed cross-application recall. The repository also lists an OpenClaw plugin and an open model, Hy-Memory-30B-A3B, on Hugging Face.